RESEARCH: CANCER
FOLDING PROJECT #14932 PROFILE
PROJECT TEAM
Manager(s): Prateek BansalInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 105,129Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project looks at Class F Receptors, which help control how cells develop. When these receptors are overactive, it can lead to cancers like Basal Cell Carcinoma and Medulloblastoma. By using computer simulations, researchers hope to learn how these receptors work so they can better understand and treat these diseases.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Class F Receptors Class F Receptors are involved in the control of cell differentiation.
Over-activation of these proteins have links to Basal Cell Carcinoma and Medulloblastoma.
Through Simulations we aim to understand the activation mechanisms of these proteins, giving us a way to probe into the pathogenesis of the disease.
RELATED TERMS GLOSSARY AI BETA
Class F Receptors
A family of G protein-coupled receptors involved in cell differentiation.
Class F Receptors are a type of protein found on the surface of cells. They play a crucial role in regulating how cells develop and specialize. When these receptors are overactive, it can lead to the development of certain cancers, such as Basal Cell Carcinoma and Medulloblastoma. By studying how these receptors work, researchers hope to find new ways to treat these diseases.
Basal Cell Carcinoma
A type of skin cancer that originates in the basal cells.
Basal Cell Carcinoma is a common type of skin cancer that starts in the basal cells, which are found in the deepest layer of the epidermis. It typically appears as a pearly or waxy bump and can grow slowly over time. Treatment options include surgery, radiation therapy, and topical medications.
Medulloblastoma
A type of aggressive brain cancer that develops in the cerebellum.
Medulloblastoma is a malignant tumor that originates in the cerebellum, the part of the brain responsible for balance and coordination. It is most common in children and can spread to other parts of the body. Treatment typically involves surgery, radiation therapy, and chemotherapy.
Simulations
The use of computer models to mimic real-world processes.
Simulations are a powerful tool used in science and engineering to understand complex systems. By creating computer models that represent real-world phenomena, researchers can test hypotheses, explore different scenarios, and gain insights that would be difficult or impossible to obtain through traditional experiments.
Pathogenesis
The development and progression of a disease.
Pathogenesis refers to the biological processes that lead to the onset and development of a disease. Understanding the pathogenesis of a particular disease is essential for developing effective treatments.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:32:42|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 7,588,742 | 143,996 | 52.70 | 0 hrs 27 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,928,571 | 137,765 | 50.29 | 0 hrs 29 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 6,164,143 | 131,381 | 46.92 | 0 hrs 31 mins |
| 4 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,831,365 | 133,814 | 43.58 | 0 hrs 33 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,086,506 | 126,889 | 40.09 | 0 hrs 36 mins |
| 6 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,624,895 | 122,468 | 37.76 | 0 hrs 38 mins |
| 7 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,580,401 | 122,734 | 37.32 | 0 hrs 39 mins |
| 8 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 4,512,553 | 122,677 | 36.78 | 0 hrs 39 mins |
| 9 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,491,302 | 122,079 | 36.79 | 0 hrs 39 mins |
| 10 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 4,177,421 | 120,030 | 34.80 | 0 hrs 41 mins |
| 11 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,961,178 | 116,864 | 33.90 | 0 hrs 42 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,207,614 | 108,763 | 29.49 | 0 hrs 49 mins |
| 13 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,955,053 | 103,742 | 28.48 | 0 hrs 51 mins |
| 14 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,630,269 | 102,659 | 25.62 | 0 hrs 56 mins |
| 15 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,310,848 | 98,300 | 23.51 | 1 hrs 1 mins |
| 16 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,205,788 | 94,833 | 23.26 | 1 hrs 2 mins |
| 17 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,133,136 | 95,136 | 22.42 | 1 hrs 4 mins |
| 18 | GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB] |
Nvidia | TU106 | 2,091,295 | 93,007 | 22.49 | 1 hrs 4 mins |
| 19 | GeForce RTX 3060 GA106 [GeForce RTX 3060] |
Nvidia | GA106 | 2,085,360 | 95,319 | 21.88 | 1 hrs 6 mins |
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| 20 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,021,064 | 93,809 | 21.54 | 1 hrs 7 mins |
| 21 | GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186 |
Nvidia | GP104 | 1,448,406 | 84,648 | 17.11 | 1 hrs 24 mins |
| 22 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,367,249 | 82,389 | 16.60 | 1 hrs 27 mins |
| 23 | GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q] |
Nvidia | TU106M | 1,308,036 | 81,730 | 16.00 | 1 hrs 30 mins |
| 24 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,148,637 | 77,573 | 14.81 | 1 hrs 37 mins |
| 25 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,108,121 | 77,003 | 14.39 | 1 hrs 40 mins |
| 26 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,046,244 | 74,201 | 14.10 | 1 hrs 42 mins |
| 27 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,009,930 | 74,243 | 13.60 | 1 hrs 46 mins |
| 28 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 721,323 | 65,660 | 10.99 | 2 hrs 11 mins |
| 29 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 586,048 | 62,846 | 9.33 | 2 hrs 34 mins |
| 30 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 573,187 | 61,821 | 9.27 | 2 hrs 35 mins |
| 31 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 561,219 | 60,958 | 9.21 | 2 hrs 36 mins |
| 32 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 470,080 | 57,759 | 8.14 | 2 hrs 57 mins |
| 33 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 418,153 | 54,022 | 7.74 | 3 hrs 6 mins |
| 34 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 325,028 | 51,443 | 6.32 | 3 hrs 48 mins |
| 35 | GeForce GTX 960 GM206 [GeForce GTX 960] 2308 |
Nvidia | GM206 | 309,196 | 50,376 | 6.14 | 3 hrs 55 mins |
| 36 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 301,637 | 50,062 | 6.03 | 3 hrs 59 mins |
| 37 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 226,949 | 45,249 | 5.02 | 4 hrs 47 mins |
| 38 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 146,194 | 39,158 | 3.73 | 6 hrs 26 mins |
| 39 | GeForce GTX 680 GK104 [GeForce GTX 680] 3250 |
Nvidia | GK104 | 125,340 | 37,364 | 3.35 | 7 hrs 9 mins |
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| 40 | GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634 |
Nvidia | GK104 | 98,619 | 34,528 | 2.86 | 8 hrs 24 mins |
| 41 | GeForce GTX 660 GK106 [GeForce GTX 660] |
Nvidia | GK106 | 68,000 | 30,496 | 2.23 | 10 hrs 46 mins |
| 42 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 50,936 | 27,725 | 1.84 | 13 hrs 4 mins |
| 43 | GTX 650 Ti Boost GK106 [GTX 650 Ti Boost] |
Nvidia | GK106 | 43,041 | 22,243 | 1.94 | 12 hrs 24 mins |
| 44 | GeForce GT 730 GK208B [GeForce GT 730] 692.7 |
Nvidia | GK208B | 15,400 | 16,800 | 0.92 | 26 hrs 11 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:32:42|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|